The development of a scientific field is often punctuated by a period when diverse observations can be understood in terms of a set of unifying principles. This important moment in time occurs when a critical number (and type) of observations becomes available, and the mechanistic principles often result from an amalgamation of ideas drawn from different intellectual disciplines. This period also marks the emergence of predictive models. T lymphocytes (T cells) orchestrate (and can also misregulate) the adaptive immune response. I believe that T cell biology, especially T cell-mediated autoimmunity, is at a critical juncture where diverse data will soon be integrated in terms of overarching principles. Modern experiments are revealing, in unprecedented detail, the factors that are important in the emergence of T cell-mediated autoimmunity rather than tolerance to ?self?. However, general mechanistic principles necessary for predictive models have proven elusive. This is because T cell-mediated autoimmunity is characterized by cooperative dynamic processes that occur over a spectrum of length and time scales. Phenomena occurring on large scales (tissues) influence cooperative molecular events in a single T cell which, in turn, influences the tissue environment. This complex hierarchical cooperativity makes it difficult to intuit underlying mechanisms from experimental observations alone. I propose to develop the principles governing T cell-mediated autoimmunity by parsing the pertinent cooperative dynamics which occur in a complex space of molecular and cellular variables by integrating three great advances of the twentieth century: statistical mechanics, computational technology, and genetic, biochemical, and imaging experiments. A key to success will be collaborations with experimental immunologists, and I have recently demonstrated how such synergies can be fruitful. If successful, the work that I envisage will provide the principles that could guide the development of therapies for diseases such as multiple sclerosis and diabetes which afflict millions of people.